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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
computer science
K-Means-Type Algorithms: A Generalized Convergence Theorem and Characterization of Local Optimality
IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume PAMI-6, No. 1, Year 1984
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Description
The K-means algorithm is a commonly used technique in cluster analysis. In this paper, several questions about the algorithm are addressed. The clustering problem is first cast as a nonconvex mathematical program. Then, a rigorous proof of the finite convergence of the K-means-type algorithm is given for any metric. It is shown that under certain conditions the algorithm may fail to converge to a local minimum, and that it converges under differentiability conditions to a Kuhn-Tucker point. Finally, a method for obtaining a local-minimum solution is given. © 1984 IEEE.
Authors & Co-Authors
Selim, Shokri Z.
Saudi Arabia, Dhahran
King Fahd University of Petroleum and Minerals
Ismail, Mohamed A.
Canada, Windsor
University of Windsor
Statistics
Citations: 1,232
Authors: 2
Affiliations: 2
Identifiers
Doi:
10.1109/TPAMI.1984.4767478
ISSN:
01628828